Daniel Quevedo

Professor Daniel Quevedo is a leading academic in Electrical and Computer Engineering at The University of Sydney. Previously, he held positions at Queensland University of Technology and Paderborn University, Germany, where he founded the Chair in Automatic Control. He earned his PhD from the University of Newcastle (Australia) and MSc/Ing. degrees from Universidad Técnica Federico Santa María (Chile).

His research focuses on networked control systems, cyber-physical systems, and cybersecurity, with contributions to state estimation, control of power converters, and human-in-the-loop systems. He has pioneered work integrating machine learning, behavioral economics, and advanced mathematics to address challenges in interconnected digital-physical environments.

Quevedo serves as Associate Editor for IEEE Transactions on Control of Networked Systems and IEEE Control Systems. He chairs the Committee of Experts for Germany’s Excellence Strategy on Digital Methods and has held leadership roles in IEEE technical committees. Notable awards include the IEEE Axelby Outstanding Paper Award (2018) and multiple fellowships.

Teaching includes advanced control systems courses like Reinforcement Learning and Optimal Control. He is a Fellow of the IEEE and has published over 200 peer-reviewed articles, with recent work emphasizing privacy-preserving state estimation, resilient control systems, and energy-efficient wireless control.

His research labs explore topics such as human-machine collaboration, cybersecurity in Industry 5.0, and data-driven control strategies. Current projects include secure remote state estimation frameworks and adaptive control under adversarial conditions.